Functional organization of the yeast proteome by a yeast interactome map.

It is hoped that comprehensive mapping of protein physical interactions will facilitate insights regarding both fundamental cell biology processes and the pathology of diseases. To fulfill this hope, good solutions to 2 issues will be essential: (i) how to obtain reliable interaction data in a high-throughput setting and (ii) how to structure interaction data in a meaningful form, amenable to and valuable for further biological research. In this article, we structure an interactome in terms of predicted permanent protein complexes and predicted transient, nongeneric interactions between these complexes. The interactome is generated by means of an associated computational algorithm, from raw high-throughput affinity purification/mass spectrometric interaction data. We apply our technique to the construction of an interactome for Saccharomyces cerevisiae, showing that it yields reliability typical of low-throughput experiments from high-throughput data. We discuss biological insights raised by this interactome including, via homology, a few related to human disease.

Yeast Protein Interactome topology provides framework for coordinated-functionality.

The architecture of the network of protein-protein physical interactions in Saccharomyces cerevisiae is exposed through the combination of two complementary theoretical network measures, betweenness centrality and 'Q-modularity'. The yeast interactome is characterized by well-defined topological modules connected via a small number of inter-module protein interactions. Should such topological inter-module connections turn out to constitute a form of functional coordination between the modules, we speculate that this coordination is occurring typically in a pairwise fashion, rather than by way of high-degree hub proteins responsible for coordinating multiple modules. The unique non-hub-centric hierarchical organization of the interactome is not reproduced by gene duplication-and-divergence stochastic growth models that disregard global selective pressures.

The Universal Non-Neuronal Nature of Parkinson's Disease: A Theory.

Parkinson's disease (PD) is one of the most common neurodegenerative disorders, yet the etiology of the majority of its cases remains unknown. In this manuscript, relevant published evidence is interpreted and integrated into a comprehensive hypothesis on the nature, origin, and inter-cellular mode of propagation of sporadic PD. We propose to characterize sporadic PD as a pathological deviation in the global gene expression program of a cell: the PD expression-state, or PD-state for short. A universal cell-generic state, the PD-state deviation would be particularly damaging in a neuronal context, ultimately leading to neuron death and the ensuing observed clinical signs. We review why ageing associated accumulated damage caused by oxidative stress in mitochondria could be the trigger for a primordial cell to shift to the PD-state. We propose that hematopoietic cells could be the first to acquire the PD-state, at hematopoiesis, from the disruption in reactive oxygen species homeostasis that arises with age in the hematopoietic stem-cell niche. We argue that cellular ageing is nevertheless unlikely to explain the shift to the PD-state of all the subsequently affected cells in a patient, thus indicating the existence of a distinct mechanism of cellular propagation of the PD-state. We highlight recently published findings on the inter-cellular exchange of mitochondrial DNA and the ability of mitochondrial DNA to modulate the cellular global gene expression state and propose this could form the basis for the inter-cellular transmission of the PD-state.

Recent advances in the development of an inhaled insulin product.

Inhaled insulin first entered clinical human testing in the mid 1990s. Since then, the commercial potential and technical challenges of an inhaled insulin product have grown increasingly clear, with several pharmaceutical partnerships now targeting treatment of diabetes mellitus through inhalation products in clinical development. While clinical results to date show the therapy to be generally promising, recent data have raised questions related to human safety and slowed progress toward a commercial product. Answering these questions positively in the coming years will be critical to making inhalation therapy a practical diabetes-care reality.

Biological insight, high-throughput datasets and the nature of neuro-degenerative disorders.

Life sciences are experiencing a historical shift towards a quantitative, data-rich regime. This transition has been associated with the advent of bio-informatics: mathematicians, physicists, computer scientists and statisticians are now commonplace in the field, working on the analysis of ever larger data-sets. An open question regarding what should drive scientific progress in this new era remains: will biological insight become increasingly irrelevant in a world of hypothesis-free, unbiased data analysis? This piece offers a different perspective, pin-pointing that biological thought is more-than-ever relevant in a data-rich setting. Some of the novel highthroughput information being acquired in the field of neuro-degenerative disorders is highlighted here. As but one example of how theory and experiment can interact in this new reality, our efforts in developing an idiopathic neuro-degenerative disease hematopoietic stemcell ageing theory are described.

Rare coding SNP in DZIP1 gene associated with late-onset sporadic Parkinson's disease.

An association between a rare, coding, non-synonymous SNP variant in the gene DZIP1 and Parkinson's disease was found, based on an analysis of the existing NGRC genome-wide association study dataset. The statistical analysis utilized the hypothesis-rich, targeted search unbiased assessment approach, rather than the hypothesis-free, genome-wide agnostic search paradigm. The association of DZIP1 with Parkinson's disease is discussed in the context of a Parkinson's disease stem-cell ageing theory.

Genome-wide association study heterogeneous cohort homogenization via subject weight knock-down.

Population structure can be a source of both false-positive and false-negative findings in a genome-wide association study. This article proposes an approach that helps to reduce the false-positives. It consists of homogenizing the diseased/healthy phenotype ratio across the cohort, by decreasing the statistical weight of selected individuals. After homogenization, the cohort is statistically handled as if originating from a single well-mixed population. The method was applied to homogenize a Parkinson's disease genome-wide association study cohort.

Epigenetic engineering to reverse the Parkinson's expression state.

Nature, initiation and ensuing cellular propagation mode of sporadic Parkinson's disease (comprising over 90% of all Parkinson's cases) remain open research questions. Accordingly, so does the best therapeutic avenue for addressing this debilitating disease that today affects an estimated 7-10 million people worldwide. Recently, we argued that sporadic Parkinson's be fundamentally characterized as a pathological deviation from normality in the expression program of a cell, the PD-state. Further, we suggested this generic cell state (not restricted to neurons) could be epigenetically locked-in. This raises the theoretical possibility of reverting a cell's PD-state to normality by appropriate epigenetic reprogramming. In here, we propose an in vitro relatively high throughput search for a cocktail of molecules that induces an epigenetic reversal of the PD-state. A generic multi-tissue PD-state phenotype appears to be a defect on mitochondrial bioenergetics. In the above search, we suggest utilizing a metabolic challenge as a preliminary screen for assessing, via improvement of energy metabolism, reversal of the PD-state.

POLAR MAPPER: a computational tool for integrated visualization of protein interaction networks and mRNA expression data.

Polar Mapper is a computational application for exposing the architecture of protein interaction networks. It facilitates the system-level analysis of mRNA expression data in the context of the underlying protein interaction network. Preliminary analysis of a human protein interaction network and comparison of the yeast oxidative stress and heat shock gene expression responses are addressed as case studies.

Two-peak and three-peak optimal complex networks.

A central issue in complex networks is tolerance of random failures and intentional attacks. Current literature emphasizes the dichotomy between networks with a power-law node connectivity distribution, which are robust to random failures but fragile to targeted attacks, versus networks with an exponentially decaying connectivity distribution, which are less tolerant to failures but more resilient to attacks. We prove analytically that the optimal network configuration under a classic measure of robustness is altogether different from both of the above: in all cases, failure and/or attack, there are no more than three distinct node connectivities in the optimal network.